Embodiments of the invention are directed, in general, to imaging devices and methods, more specifically to estimate compression noise of decompressed images for known statistics.
Modern medicine cannot be envisaged without the aid of digital imaging. Daily, large amounts of images are obtained from two-dimensional (2D), three-dimensional (3D), four-dimensional (4D—time/space), and multidimensional acquisition devices (i.e. X-ray computed tomography (CT), magnetic resonance imaging (MRI), confocal microscopy, ultrasound imaging, single photon emission computed tomography (SPECT) and positron emission tomography (PET)). While CT and MR acquisition devices still represent a big investment, ultrasound equipment is more accessible for home practitioners and will probably become more and more popular. All these digital images need to be efficiently stored, exchanged and processed. Therefore, recently high performance lossless and lossy compression (decompression) algorithms have been developed. Most of these algorithms are based on transform coding (e.g. JPEG is DCT based coding scheme) or subband coding (e.g. JPEG 2000 is wavelet based coding scheme) and have been tuned in terms of speed and quality with respect to compression ratio.
With lossy compression algorithms, compressed images can be exchanged more efficiently, i.e. more data can be available for the same storage capacity, and faster transfer can be achieved via a network channel however, there is compression distortion in decompressed images. Compression noise statistics represent the compression distortion. This patent teach how to estimate compression noise statistics. In medical applications, medical imaging has started to take advantage of digital technology and open the way for advanced medical imaging, tele-radiology, tele-medicine, and even tele-surgery.
Medical images require large amounts of data storage. For example, one digital mammogram with 50 micron resolution and a 12 bit dynamic range requires 25 MB, and there are usually four images for each patient exam. The requirements for large storage space and high transmission bandwidth have become major issues for medical imaging. Diagnostic telemedicine is revolutionizing the medical imaging industry, which is facing the challenge to provide image compression with not only high quality but also high compression ratio to have cost-effective storage and transmission. Therefore, one crucial research area is to assess the impact of image compression on diagnostic accuracy. The compression noise statistics can be used to estimate the impacts.
Because of advances in miniaturization and cost-reduction in the semiconductor art, certain devices for tele-medicine and other uses have become small enough to be portable or wearable. These compact devices typically comprise sensors for collecting data, a processor for manipulating data, and a graphical display for showing real-time information. An example of portable imaging device is provided by U.S. Pat. No. 6,417,797, issued on Jul. 9, 2002, to Cousins et al. Said patent incorporated by reference.
Similarly, in forensic crime scene investigations and concealed object detection, there is a need to locate, identify and analyze anomalies or patterns in an image-like data set.
There is a need for a more processor efficient method to estimate compression distortion which can provide compressed image quality assessment, compression algorithm optimization, compression noise reduction, and other quantization and compression related applications.